I just want to run a container...

 ...is a developer-centric point of view?

Generic data center image to exemplify a place many of us have never set foot into.

After a few hours spent on upgrading the toolchain that starts from Terraform, goes through a few AWS-maintained modules and reached the Elastic Kubernetes Service APIs, my team was entertaining the thought of how difficult it is to set up infrastructure. Infrastructure that, for this use case takes a container image of a web application that Docker generated and run it somewhere for users to access.

Thinking through this, either Kubernetes is the new IBM (no one ever get fired for choosing it), or there is more to a production web application than running a container which is what Kubernetes is often sold as: a tool to run containers in the cloud without the necessity to set up specific virtual machines, but treating them as anonymous, sacrificeable nodes where the aforementioned containers can be tightly packed and sharing CPU, memory and other resources.

What exactly is the infrastructure doing for us here? There are a few concerns about operations, the other side of that magic DevOps collaboration. For example:

• the container image is exposing an HTTP service on port 80. This is not useful for a modern browser and its padlock icons, so to achieve a secure connection a combination of DNS and Let's Encrypt generated and automatically renews certificates after verifying proof of ownership of our domain name.
• the container image produces logs in the form of JSON lines. Through part of the Grafana stack, these lines are annotated with a timestamp, the container that generated them and various labels such as an environment or the name of a component of the application (think frontend or prod or staging). After these lines are indexed, further software provides the capability to query these logs, zooming in on problems or prioritizing errors during investigation.
• if we get too much of these logs at the level of error for a particular message, we'd like to receive an alert email that triggers us into action.
  
• invariably applications benefit from scheduled processes that run periodically and independently from the request/response lifecycle. It's such a useful architectural pattern that Kubernetes even named a resource after the cron daemon, introduced in 1975.
• it's also very useful for applications to maintain state and store news rows in a relational database. Provided turnkey by every cloud, a set of hostname, username and password allows access from any combination of programming language and library. No need to worry about rotating the logs of Postgres anymore, or that we are running out of space.
• the data contained in the application and generated by user also lends itself to timely analysis, so that we know whether to kill a feature or to invest in it. This means somehow taking out recent updates (or whole tables) into a data pipeline that transforms it into something that can be analyzed by a data scientist. All with an acceptable speed.
• Those credentials nevertheless need to be provided to the application itself, hopefully without accidentally disclosing them into chats, logs, or emails. No human should need to enter them into an interface.
• Configuration is slightly easier to manage than credentials due to the lack of sensitive values, but we'd still like the capability to generate some of these values such as a canonical URL or to pass in different numbers for different environments.
  
• And of course, whenever we commit, we'd like to deploy the change and start the latest version of our application, check that it is responding correctly to requests, and then stop the old, still running one.

This is all in the context of a single team, running operating a single product. Part of this is achieved through running off-the-shelf software on top of Kubernetes; part of it by paid-for cloud services; part of it by outsourcing to a specialized software as a service.

However, when we think about software development we don't necessarily think about software operations. Many of us started our careers by writing code, testing and releasing it without a further look to what was happening afterwards. DevOps as a philosophy meant bridging the gaps; You Build It You Run It is the easiest summary for me.

Yet what I see and what I hear from experienced people is that silos in infrastructure seriously slow teams down, and create fears of insurmountable problems. Abandoned projects, "finished" from a development point of view, but now having unclear ownership and running in production supporting the main revenue stream of an organization.

So I don't want to just run a container. I'd rather deploy many incrementally improved versions of a container, monitor its traffic and user activity, and close the feedback loop that links usage to the next development decision.

In other words: I can always build simple code if it doesn't have to run in production.

A year of mob programming, part 5: methodology

I wouldn't call mob programming a methodology, but rather a practice that can be adopted. Like methodologies, however, it only surfaces problems and questions faster rather than providing solutions.

For example, a team might have a low bus factor due to the specialisms of its members, and only one person might be used to edit code in a certain language or application. Other team members might have gaps, such as not being set up with the tools and credentials to work on infrastructure and operations; or lacking the knowledge to perform screen reader testing for accessibility.

Besides exposing bus factors and gaps, mob programming brings design conflicts and opinions into the open. It takes little effort to turn the other way when looking at a pull request, or to switch to busy work or generic "refuctoring" when alone; disagreements and questions about value can often prop up under your nose inside a mob session.

However, that doesn't mean that the practice automatically gives the team the psychological safety to talk about those issues out loud, and to resolve them. That's like asking an hammer to walk to the shop and buy the right nails.

At the last part of this post, I thought I'd compare my mob programming experience with some of the theory; the theory being famous Agile software development methodologies and their values or principles.

The serene predictability of waterfall software development

Within Extreme Programming values:

• Communication inside a mob is very high: synchronous conversations supported by a visual medium such as code or a digital whiteboard.
• Simplicity is fostered by people in a diverse team reminding others that You Aren't Gonna Need It, but also needing to understand what's going on at all times.
• Feedback from the rest of the team, or even from a customer proxy, is immediate.
• Courage is needed to be a driver in an unfamiliar setting, or even a navigator asking the mob for help on a task we are uncomfortable with.
• Respect is necessary to work face to face for prolonged periods of time.
  

Within Lean values, mob programming:

• eliminates waste such as partially done work: there should ideally be no pull request open or branch, as code is produced and integrated in the mob continuously;
• eliminates waste such as outdated features or gold plating: when you include a product owner in the mob, it's easy to steer and change the scope upon feedback rather than plowing on with the original idea;
• eliminates waste such as handoffs: there is no packaging up of code for review, or of pixel-perfect Photoshop design to front end developers, or front end requests to back ends to be implemented, and so on.
• reduces task switching: since everyone that is needed for progress is present, you often don't need to switch task because of waiting on someone, but can just carry on.
• amplifies learning: ideas are tried out in code from the get go, and most of the team can learn from the results including the product owner.
• optimizes the whole: most of all, we are not optimizing how much we can use everyone's time, but how fast we can flow a single piece from idea to customer value.

Image by Yann.

A year of mob programming, part 4: the remoteness of it

I don't have a frame of reference for mob programming in a co-located environment, besides conference (or team exercise) workshops that didn't involve production code.

On a video call, the driver is still always explicitly defined as the person sharing their screen and tools. This is similar to the person physically having the keyboard when you are all sitting around a table.

The navigator can either be more implicit, move around or be strictly defined by a process. If an implicit navigator doesn't emerge for the current commit, it should be considered normal to quickly nominate one as needed. Over time, we normalize the phrase "can you navigate [that change]?" in response to a proposal.

Due to latency, in a video call environment there is a sort of Lorentz time where you may hear overlapping voices when someone else doesn't, and vice versa. It all depends on how much latency each video link is experiencing, and the adjustments that software makes can be jarring, such as video freezes or audio being delivered 10-20 seconds later.

"Sorry, two people talking over each other" "Really??"

I'm sure though everyone has already experienced people talking over each other in a physical room: it isn't exclusively a remote working problem and relies on team interactions more than technology.

We also want to communicate and especially give feedback through voice, as people's faces are not always visible to a driver looking at code; nodding doesn't necessarily help.

Perhaps a bigger problem is the fact that video calls don't allow side conversations to happen, as there is a single audio channel that our ears cannot separate into directions. This is likely to impact a massively parallel EventStorming around a whiteboard, less so an ensemble of 3-4 people trying to get to a consensus on their next move. The side conversations however include those famous water cooler talks, bumping into people in the kitchen or while on a break.

Your theory of mind might have more trouble cutting through the limited signal, and understand in what mental state other people in the team are; and whether today's problem is more due to Internet connection trouble, or a real conflict between team members. The daily retrospective helps to let people put tools down, and reflect on the day; possibly proposing experiments for the next session. 

Looking at the world around me, I'm quite sure I would be as depressed by remote work as many, if it consisted of me being alone for most of the day. So due to mob programming I have a different perspective on how incredibly engaging working from home can be.

Stay tuned for the next (and last) part of this post, Methodology.

Image by Duesentrieb.

A year of mob programming, part 3: a laboratory for team dynamics

Our implementation of mob programming consists in a permanent Google Meet videocall, with camera on, in which we rotate a developer sharing a screen containing IDE and browser. So there are two unusual practices to get used to: being in a group all the time, and being on a camera all the time.

I was originally surprised on how both practices went from exhausting to being a normal work day. This is my experience, and we have to consider neurodiversity and personal preferences in the team on having a long screen time and continuous social interaction. It's almost obvious to say, but sometimes people hate inconclusive meetings in which they have no say; not being together with other human beings.

Don't underestimate your capacity to adapt, but recognize that your energy is not going to always be the same; whether because you got a cold, or something is going on at home, or some task is particularly draining. 

The Flemish inscription at bottom reads: because feedback is perfidious, I will go code in my cave

Gold cards and spike branches give people the ability to work on their own when they request to. Mechanical work such as upgrade of dependencies or investigating logs can benefit from focused time from one person. If you were in an office, you could go to an isolated room; working remotely, it's even easier as it just consists in leaving the video call and coming back refreshed later.

The opposite can also happen, when someone like me can manifest Fear Of Missing Out and the mob making lots of decisions in their absence. As the team gets to a norming phase, we should expect fewer surprises for members coming back to the mob after some time off.

Being together with the rest of the team can make your motivation higher due to the group support in getting started or unstuck from a particular problem; but of course the whole group can struggle on occasion.

Every time there is a new composition, though, there are changes in how the mob is working and what it pays more attention to. And from the point of view of a growing team leader, being embedded in a mob environment means being positively inundated with information. The challenge is to make sense of what we see to understand where team members are struggling and what are they finding most effective.

"I wish I could see players only in 121 meetings" -- No football coach ever

This requires a lot of (cognitive) bandwidth, and I usually can't at the same time focus on technical architecture and on social roles. But maybe this is just an argument to work in a team where the different hats can be rotated; as much as there is always someone writing code, there can always be someone checking if we have started to talk over each other, or we are falling into a rabbit hole of an hour without committing.

Stay tuned for the next part of this post, The remoteness of it.

Images by Michael Kranewitter and in the public domain.

A year of mob programming, part 2: Collective Code Ownership

With respect to a team assigning tasks to developers by their function (frontend, backend, infrastructure, and so on), mob programming fosters Collective Code Ownership.

This is more in the sense that everyone should be able to contribute through the mob in any area, rather than everyone being able to prioritize on their own what needs to be improved. The pact is that our time belongs to the team, and the team decides what is important.

A result of this is an healthy prevention of knowledge silos, where you can exercise your own creativity just because no one else knows how to work in that area anymore.

Code review happens continuously in the mob on small changes, and there are no huge feature branches to go through. In large changes such as those, it's too late for review to suggest a valuable but completely different approach; there is too much investment of time and energy into code. If review dares to suggest groundbreaking changes, it causes extensive rework instead.

There is a larger picture on ownership: team members tend to keep track of what they care about, whether that is consistency in architecture, front end approaches to styling, performance issues, and so on.

Sometimes I found myself being talked out of a design I had in mind, counteracting bias I could have for the first or most familiar solution. I started working on this team with an object-oriented mindset, but we have transitioned to functional programming in TypeScript.

Sometimes, there are hills to die on: hard to reverse decisions on architecture, or programming language choices. It's a job of a psychologically safe team to discuss these choices collectively without drama or oversimplification like JavaScript being the the death of computer science. 

"I told you we should have written the code in English, not Latin!"

It tooks three different iterations to get a repeatable pattern for accepting Commands (as in CQRS). But it was more fruitful to focus on the Domain Events design, as a difficult choice to revisit, than on the shape of the code itself which can be refined at any time.

Working outside of the mob

The counterpart to the XP mantra of writing all production code in pairs (or a mob) is to allow team members to contribute when they are working alone due to other necessities, such as an unstable Internet connection or a flexible day where they can't align completely with the core hours of the team.

I have learned to ask the team to be commissioned something to do, or at least to give them a choice. This keeps the prioritization in the hands of the group, again reducing bias.

It's helpful to assign problems that have only a constrained possible solution such as renaming, or propagating a refactoring through the codebase for consistency's sake.

It also helps to report back what you have learned during a solo coding exercise when rejoining the mob; unexpected issues or decisions you had to take on the spot and you feel unsure about.

You're allowed to stop at a certain point, as making progress alone at all costs is valued less than maintaining collective code ownership and a shared understanding of how our application works.

Technical spikes can also be chosen by a single person to work on, either because they want to individually prioritize them to demonstrate an idea; or because the amount of investigation required makes it difficult or frustrating to collaborate.
Spikes can be built on throwaway branches, being optimized for learning rather than for delivering production quality code. Once an idea has been demonstrated and approved, the mob can implement it pretty quickly on the trunk, and if we believe in the practice, with an higher level of quality. I constantly find feature branches worked by a single person to be a dead end (especially if they are my own).

In the end, people are frequently in meetings, researching or even just on holiday for a given day. Hence there's always someone missing that will catch up on the progress when they come back into the mob. But the group itself never stops even as the components change, so some of that progress will happen every day, other things being equal.

Stay tuned for the next part of this post, A laboratory for team dynamics.

Image by Johann Jaritz.

A year of mob programming, part 1: metaphors

I've been practicing remote mob programming in my team for more than a year, writing more than 90% of production code inside a video call with multiple developers looking at the same screen.

A bit of context

I work in the scientific publishing domain, on web applications oriented to help scientists throughout their day.

My current team has been formed from the start as a remote team, and has been working with mob programming for more than a year. It is a cross-functional team that is including a product manager and often a designer into the (virtual room) for co-creation.

Our set of technologies includes TypeScript, lots of semantic HTML, and minimal client-side JavaScript. Container-based infrastructure and databases are pulled in as required by the evolution of the product.

This is an experience report, not advice that can be applied blindly to your team or organization.

Metaphorical definitions

All the brilliant people working on the same thing, at the same time, in the same space, and on the same computer -- Woody Zuill

Like pair programming, mob programming can be simplistically explained through the metaphor of driving a car in a rally. Or at least, that's how I always understood the driver and navigator pair.

• A driver shares their screen and has sole access to the keyboard. They are an intelligent IDE capable of executing mechanical refactoring and fixes, but not of deciding a design direction for the code.
• A navigator verbalizes what the driver should be doing, making decisions that reach down to what test or line of code to write.
• The rest of the group is on the back seat of the car, and can speak at will, volunteering information to the navigator or answering questions. Are we there yet?
  

The roles of driver and navigator are rotated often, in fixed time or scope increments such as on every commit. The navigator can implicitly move continuously from one person to another, as long as there isn't more than one navigator at once.

Mob as a name

Speaking Italian as a first language, the term mob doesn't necessarily evoke an emotional reaction from me. But I can recognize a term that can be used to describe organized crime might not allow team members to feel comfortable. My understanding is that mob has to be intended as crowd rather than mafia.

"This is so wasteful. Why aren't they all in separate rooms playing 4 different songs?"

Nevertheless, we looked for more metaphors and terms that can be used to talk about the group of people that work together:

• orchestra emphasizes the coordination required by a group of people, and their simultaneous presence. I'm not sure they need a conductor though.
• ensemble is a similar musical metaphor, that focuses on a small group of complementary roles closely working together.
• swarm refers to a group of bees all converging towards a single task to get it done.
• the team itself ideally coincides with the mob, though there can be non-technical roles that find difficult to contribute all the time; the mob can also be temporarily reduced from the full set of developers in the team, or multiple mobs can appear in a relatively large team.
• a womble is a fictional furry creature from children's books that helps the environment by cleaning up rubbish. It has no relation to groups whatsoever and is an unrelated word, with no unfortunate or fortunate connotations attached. We ended up using this word for a while for disambiguation.

These are all the metaphors that I've seen used to describe mobbing. Stay tuned for the next part of this post, Collective Code Ownership.

Image by Princess Ruto.

How is software like cooking?

Time for a light-hearted post. After my move to the UK and having had my share of fish and chips, I have become by reaction more interested in Italian culinary history and practice. So I started diving into the science and the tradition of cooking, reading books such as the science of meat which combine chemistry and good taste, and I have now cooked enough lasagne to build a statistically significant sample.

Disclaimer: this post is full of meat references as that's culturally significant as a metaphor to transmit the concepts I have in mind. You may find this distasteful if you have chosen to follow a different path.

So here's 5 ways in which software development and cooking are alike...

Feedback loops

"to serve man"

There's a joke in a Futurama episode about Bender (being a robot) not having a sense of taste and hence playfully disgusting the humans in the team with too much salt. The joke works because in cooking you need a continuous feedback loop to conform to your taste, for example adding salt and pepper at the end of a preparation until it tastes right.

We are no strangers to this process in software development: most of the practices I preach about lead to getting working software in front of someone that will use it as soon as possible, to better steer future development with the feedback.

There are shorter, inner feedback loops than tasting: the speed with which meat is browning will make you adjust your source of heat for that phase of the preparation to avoid charring the exterior surface to a pitch black color. Not too different from your unit tests failing and informing you of an issue well before it gets to an actual customer that will send the steak back to the kitchen.

Quality is in the eye of the beholder

Cacio e pepe: simple&tasty or poor?

Taste has lots of different components, including not just what your tongue perceives but also smells, presentation, and expectations. But for most of these aspects, quality is in the eye of the beholder and we can't avoid coming to grips with the variety of people and cultures.

Therefore, despite how good you think your burgers are, some people just don't like fat, mince meat. I appreciate Indian curries but I have some physical limits on the spiciness levels that make me almost always choose mild korma. And imagine the cultural shock of discovering I have been wrongly putting lemon in tea all my life instead of milk as the only acceptable choice.
(I know, tea doesn't even grow in Europe, but I grew up with British tea as the standard.)

We all have good intentions in thinking hard about what a user will enjoy or be productive with; but we have to recognize there is a vast variety of users and we have to design (or cook) for each of them.

Control the process, rather than micromanaging the material

This cake was fluorescent on purpose

Convection ovens are a great example of a controlled process for cooking uniformly. In the context of large pieces of meat or fish, this mainly means getting them to a uniform, high-but-not-too-high temperature to avoid overcooking. The oven fan pushes hot air all around them, heating the surface evenly. Air transfers less heat than, for example, water; so there is time for the temperature to rise across your roasting chicken rather than overcooking the outside while leaving some parts dangerously raw.

Thus for large cuts this is pretty much impossible to achieve in a pan, unless you literally cut everything into slices thin enough that they can cook quickly. The oven-based process is much more convenient as you literally abandon your tray in there, checking from time to time if it's ready with a thermometer.

Generally speaking of enterprise applications and websites, I favor a process in which we catch bugs with multiple safety nets (up to user experimentation if possible) than overdesigning for every possible problem. While you can think of possible scenarios to test endlessly, bugs are always going to happen and it's more important to have a process in place for which they will be fixed and never regress because of new automated tests. That makes your software converge to a steady, stable state like a perfectly cooked chicken.

You need to measure

That's definitely cold, not just for meat

If you want to consistently cook meat to your liking, there is no escape from using a thermometer to understand when it's ready - its center reaching a set temperature that corresponds to medium-rare (for a steak) or well-cooked (for poultry) or something else. Looking at the external color? No relation with the inside. Checking how hard it has become? Too subjective. Roast for a certain amount of time? Ignores the variability of both the ingredients and the heat source.

When we perceive part of an application as slow, we need to use a profiler to find out what functions or methods are taking the most time to execute. Making as few assumptions as possible, we collect data to point us in the right direction. Opinions don't count: your browser timings and other metrics do (if collected correctly).

You can substitute ingredients, to a certain extent

Focaccia genovese

Cornstarch and flour are used in small quantities in many recipes, with the goal of thickening a liquid. This is due to their starch content, as this carbohydrate granules swell up with water creating enough friction to transform a liquid with the viscosity of water into something that feels like cream.

If you try to use cornstarch to make bread however, you won't be able to get an elastic product as it lacks the proteins that would build gluten. Even if you use the wrong flour (cake flour as opposed to bread flour, to keep it simple), this will greatly affect the result due to the smaller percentage of proteins that it contains. Baking, both for sweet and savoury goods, require much more precision.

In software development, we have grown up with Lego bricks as a metaphor and we continuously try to swap out pieces, hiding details behind a useful abstraction that sometimes leaks. Nowadays relational databases can be queried interchangeably if you stick to standard SQL queries. But the data types for columns can be pretty different in the range they support, especially if they are somewhat more exotic like JSON and XML fields rather than integer and strings. A wise decision is still required to understand when substituting components is possible, or where some combinations will never work.

And here are 5 ways in which software development and cooking are very different...

Cooking is a repeatable process

Lots of Dutch cheese around Amsterdam

Recipes (at least the good ones) are literally the codification of a process that should be robust to external variations to get a consistent result. It's the mark of a good cook to be able to deal with variations in ingredients or tools, but unless you are up on a mountain water boils at pretty much the same temperature, and the physical transformation that your carrots undertake when they are heated is well established.

In software, every new feature is a new design to make rather than the execution of a plan. Even porting software or reimplementing it bears surprises as the platform it is running on is now different. And no one understands how long it took to produce the original version, no matter give an estimation for the new one that is being created. We have processes for understanding what a feature should do, and safely implementing it and rolling it out; but there are always land mines waiting on the path.

Cooking has some precise physical quantities you can rely on

Peppered pork fillet steak

Understood: measurement is needed in both fields. But as much as your oven oscillates around its target temperature, it is still much more precise than a developer's effort. Even without meetings and other time variables, how fast and precise we are in a certain day varies: humans aren't robots. Just how knowledgeable we are about a technology influences greatly the designing and testing phases. The Mythical Man-Month remains, well, mythical.

In the food industry, the right tools can even measure the strength of a flour, to check whether it's good for the bread you want to obtain. If you look at a technology team, measuring how many tasks per week we have completed is probably as good as it gets. There's humans involved and applying social science to a very small group probably doesn't get you very far in terms of collecting data and drawing inferences.

You can still measure other times objectively, like time to deploy: how long it takes for a commit on master to reach the production environment. We partly do this because it's important but also because it's feasible to measure. What most project managers would care about will be time from idea to complete implementation instead. But that requires estimating the length of a queue that changes all the time, and is just the first step of a creative development process with its own variations.

Determinism of the digital world

Blackberries from the garden

It's pretty difficult to get the same tomatoes, courgettes or grapes as last week, and pretty much impossible to get the same ones in-season and off-season. You can ship them in from South Africa or Australia but travel time and refrigeration can modify their contents, and thus their taste.

If you look at a physical server, it's much more similar to laboratory equipment than to a living product: you can run programs and see them always taking a similar amount of time to complete, controlling the randomness of the operating system around it. This gets eroded a bit in the cloud, where performance may be affected by your neighbors due to co-tenancy.

Timing in the kitchen

Very unstable crochembouche

Whether it is simply changing the temperature of a meat joint, or a more complex transformation like baking a cake, timing should be one of the concerns if you want to obtain a good result. I formalize this concept by thinking that it's not possible to stop time, in many cases.

Cooks know tricks like cooking eggs or rice to a certain degree, than cooling it down and finish the process later when the food has to be served; or simply reheat it if fully cooked. This works for various categories of products, but it's an ad-hoc process.

Consider the power we have in a digital world: firing up a debugger literally stops execution at some point in the life of the program, allowing us to take a look at what we want in the right context. Since the state of the program is the Matrix, we can slow it down, speed it up, and change things causing a déjà vu to your objects.

If you want to reproduce some computation, you have the tools available to build a Docker image containing all sorts of dependencies and store it for future usage. If you want to reproduce your perfect croissants, the only tools you have are a recipe and your own memories. Add the variation of ingredients and even temperature and humidity in your kitchen, and you can understand why scientific exploration needs a laboratory with its controlled conditions to be able to make progress.

Cooking equipment makes a difference

Now, grate parmesan without this...

Besides basic tools like appropriately shaped knives, a pressure cooker would make you able to reach certain results that would take a long time with an ordinary pot of boiling water. A temperature bath (I don't own one of these) can help cooking meat evenly only to then finish the process with a 2-minute searing. Even a scale is just necessary for baking, as measuring ingredients like flour by volume has a 50% margin of error due to its compressibility.

Consider how you can write code on your old laptop from the beach instead. You target an open source interpreter, and the end product will run on the same server that could accept strictly regulated banking software. As long as you can literally string bytes together, you can produce running software: everything else helps. The ephemeralization of software tools due to virtualization and the large availability of open source platforms make digital startups a reality, whereas opening a restaurant remains a capital-intensive operation.

But there's more...

The power of metaphors

Metaphors can foster understanding of a new system, or lead us ashtray. They are powerfully transmitting a mental model, but that model has its limitations and may even be less precise than a more formal model like a math analogy. But especially in complicated fields like cryptography, terms such as key and signature have popularized concepts to generation of students that would have otherwise found them very hard to think about.

I wrote this post for fun, but I stand behind most of the comparisons: that's all for now. You'll find me using an Helm to ship my containers...